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Estimation of COVID-19 fatality associated with different SARS-CoV-2 variants

Chapter
Publication Date:
2023
abstract:
SARS-CoV-2 outbreak is still one of the most important problems for public health, all over the world. However, its importance depends on the number of deaths associated with COVID-19 pathology. Therefore, the challenge can be seen from the epidemiological point of view, in terms of the number of deaths over time, within a certain population. Prevention, new medical approaches, drugs, and vaccines somehow aim at the same two objectives: to lower deaths, it is necessary to slow down infections and/or decrease fatality. Therefore, in order to monitor the importance of the problem, it is interesting to look at how fatality changes over time, in relation to different virus variants. In this chapter, historical data about the Italian situation are employed, and previously proposed statistical methods are applied to calculate the time series of daily estimates of SARS-CoV-2 fatality from the beginning of the pandemic until nowadays. Moreover, the evolution of estimates over time is discussed in correlation with the prevalence of different virus variants.
Iris type:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
COVID-19; SARS-CoV-2; statistics; mortality; case fatality rate; infection fatality ratio; virus variants
List of contributors:
Esposito, Massimo; Pota, Marco
Authors of the University:
ESPOSITO MASSIMO
POTA MARCO
Handle:
https://iris.cnr.it/handle/20.500.14243/462961
Book title:
Artificial Intelligence in Healthcare and COVID-19
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URL

https://www.sciencedirect.com/science/article/pii/B9780323905312000138
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